Triple
T7475017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurentide Ice Sheet |
E176607
|
entity |
| Predicate | meltwaterEffect |
P50125
|
FINISHED |
| Object | contributed to rapid sea-level rise during deglaciation |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: contributed to rapid sea-level rise during deglaciation | Statement: [Laurentide Ice Sheet, meltwaterEffect, contributed to rapid sea-level rise during deglaciation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meltwaterEffect Context triple: [Laurentide Ice Sheet, meltwaterEffect, contributed to rapid sea-level rise during deglaciation]
-
A.
hasMeltwaterContributionTo
chosen
Indicates that one entity contributes meltwater (from melting ice or snow) to another entity, such as a water body or hydrological system.
-
B.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
C.
materialMelted
Indicates that a material has undergone melting, transitioning from a solid to a liquid state.
-
D.
hasMeltingMechanism
Indicates that an entity possesses a specific mechanism or process by which it melts or causes melting.
-
E.
hasIceSurface
Indicates that an entity possesses or is characterized by a surface composed primarily of ice.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f41951348190a740b3957a73f825 |
completed | March 27, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:41 p.m.